Sampling distribution is a frequency distribution.a)trueb)falsec)bothd...
Systematic sampling is known for being less time-consuming and simpler compared to other methods of sampling.
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Sampling distribution is a frequency distribution.a)trueb)falsec)bothd...
Sampling distribution is a frequency distribution - True
Introduction:
The concept of sampling distribution is a fundamental concept in statistics. It helps us understand how sample statistics vary from one sample to another and how they are related to the population parameters. A sampling distribution is a distribution of a statistic obtained from different samples taken from the same population.
Sampling Distribution:
A sampling distribution is a probability distribution of a statistic based on a random sample. It tells us how the statistic varies when we take multiple random samples from the same population. The statistic can be a mean, proportion, standard deviation, or any other measure of interest.
Frequency Distribution:
A frequency distribution is a summary of data that shows the number of times each value or range of values occurs in a dataset. It displays the frequencies (counts) of different values or ranges of values in a dataset. A frequency distribution is often represented in a tabular or graphical form.
Relationship between Sampling Distribution and Frequency Distribution:
- A sampling distribution is a type of frequency distribution that shows the distribution of a statistic (e.g., mean) across different samples.
- The sampling distribution is obtained by repeatedly sampling from the population and calculating the statistic of interest for each sample. The resulting values of the statistic form a frequency distribution.
- The frequency distribution in a sampling distribution helps us understand the variability of the statistic and estimate the standard error, which measures the average amount of variability in the sampling distribution.
- The shape of the frequency distribution in a sampling distribution can provide insights into the population distribution. For example, if the population distribution is normal, the sampling distribution of the mean will also be normal regardless of the sample size.
- The sampling distribution allows us to make inferences about the population based on the statistics calculated from the samples. It helps us estimate population parameters and test hypotheses.
Conclusion:
In summary, the statement "Sampling distribution is a frequency distribution" is true. A sampling distribution is a type of frequency distribution that shows the distribution of a statistic across different samples. It helps us understand the variability of the statistic and make inferences about the population.